Evidence map›Paper›PMID 39762354›Full record

ArticleScientific reports2025

Bioinformatics approaches to multi-omics analysis of the potential of CDKN2A as a biomarker and therapeutic target for uterine corpus endometrial carcinoma.

Liang Ma, Yuling Li, Jingxian Wu, Yanfei Gao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Liang Ma *Department of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, 400000, China.
Yuling Li *Biochemistry and Molecular Biology, College of Basic Medical Science, Chongqing Medical University, Chongqing, 400000, China.
Jingxian WuDepartment of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, 400000, China. wujingxian@cqmu.edu.cn.
Yanfei GaoBiochemistry and Molecular Biology, College of Basic Medical Science, Chongqing Medical University, Chongqing, 400000, China. ygao@cqmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uterine corpus endometrial carcinoma (UCEC) is a significant cause of cancer-related mortality among women worldwide. Prior research has demonstrated an association between cyclin-dependent kinase inhibitor 2 A (CDKN2A) and various tumors. As a member of the INK4 family, CDKN2A is involved in cell cycle regulation by controlling CDKs. In the present study, bioinformatics was used to analyze public datasets. The expression levels, signaling pathways, and copy number variations of CDKN2A in UCEC were explored, along with its immune cell subset associations. CDKN2A expression was found to be elevated in UCEC, particularly in the signaling pathways involved in cell proliferation and inflammation. Analysis of somatic copy number alterations in the TCGA (The Cancer Genome Atlas)-UCEC dataset revealed a connection between CDKN2A and drug metabolism in UCEC. Assessment of the relationship between CDKN2A and genes involved in immunotherapy for UCEC patients showed a negative correlation between CDKN2A and CD8

Indexed as

Biomarkers, TumorComputational BiologyCyclin-Dependent Kinase Inhibitor p16Endometrial NeoplasmsGene Expression Regulation, NeoplasticCD8-Positive T-LymphocytesDNA Copy Number VariationsFemaleHumansInterleukin-2MultiomicsPrognosisSignal TransductionTumor Suppressor Protein p53Biomarkers, TumorCDKN2A protein, humanCyclin-Dependent Kinase Inhibitor p16Interleukin-2Tumor Suppressor Protein p53CDKN2ACDKN2A expressionImmunotherapySomatic copy number alteration analysisUterine corpus endometrial carcinoma

Identifiers

PMID39762354
PMCPMC11704072

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.